Abstract: Among the most prolific of signals that we deal with are speech and music, one being information rich and the other emotion (feelings) rich, along with sharing some of the characteristics between each other. Both types of signals are highly dynamic in nature, exhibiting a lot of variability due to individual characteristics of expression and style, in spite of underlying structural conventions. Stochastic models have been very successful in representing such variability in the signal patterns, along with structural variability also (as seen in speech models). Indian art-music (classical) is considered very structured and also practiced with high rigor, along with certain freedom for individual artistic expression. We examine the stochastic approaches in the literature to analyze Indian art-music and present our approach to estimate /shadja/, /swara/ and /rAga/, in an unsupervised manner. Through these models we draw parallels between the structure of speech and music signals and aim to explore the cognitive differences in the learning of speech and music.

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